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摘要： GlobeLand30-2010（30 m）、FROM-GLC-2010（30 m）和GlobCover-2009（300 m）是3套应用广泛的全球高精度土地覆盖数据产品。以巴基斯坦为研究区，从2009~2011年30 m Landsat-5、Landsat-7多光谱遥感影像共122景选取了夏冬两季各1 000个样本点，评价了3套土地覆盖数据产品的季节性分类精度。结果表明：3套产品在巴基斯坦地区夏冬两季总分类精度差异不大，总体来说GlobeLand30-2010（63.9% vs. 65.6%）与FROM-GLC-2010（59.0% vs. 61.2%）的总精度夏季略高于冬季，GlobCover-2009的总精度冬季略高于夏季（59.5% vs. 59.1%）。此外，3套产品中GlobeLand30-2010对耕地、人造地表和水体有更好的分类效果，FROM-GLC-2010对植被和冰川积雪的分类更为准确，GlobCover-2009对裸地的分类更为准确；3套产品对耕地、裸地和冰川积雪分类更符合冬季的真实情况，对植被、水体分类更符合夏季的真实情况，人造地表分类无明显的季节差异。巴基斯坦土地覆盖精度评价的样本点密度应达到1个/1 000 km2。 关键词： 土地覆盖数据产品;  精度分析;  季节性;  样本点;  巴基斯坦     Abstract: Global land cover datasets play an important role in the fields of ecology, climate and resources. GlobeLand30-2010 (30 m), FROM-GLC-2010 (30 m) and GlobCover-2009 (300 m) are three global high-precision land cover datasets with a wide range of applications. In order to judge whether these data sets are sufficient to describe the real situation of land cover in different seasons, the inter-seasonal accuracy of the aforementioned three global land cover datasets using Pakistan as a representative study area was evaluated. A total of 1 000 land cover sample points were selected from 122 Landsat-5, Landsat-7 multi-spectral remote sensing images during 2009~2011 to generate summer and winter land cover classifications.The results show that the accuracies of summer and winter land cover classifications are different in Pakistan. The overall land cover classification accuracies of GlobeLand30-2010 (65.6% vs. 63.9%) and FROM-GLC-2010 (61.2% vs. 59.0%) in summer are slightly higher than those in winter. The overall accuracy of GlobCover-2009 (59.5% vs. 59.1%) in winter is slightly higher than that in summer. GlobeLand30-2010 performs best in classifying cropland, impervious surface, and water body, FROM-GLC-2010 performs best in classifying vegetation, glaciers, and snow, and GlobCover-2009 performs best in classifying bare land. The classification of cropland, bare land, glaciers, and snow in the three datasets is more in line with the real situation in winter than in summer; the classification of vegetation and water bodies is more in line with the real situation in summer; there is no obvious seasonal difference in impervious surface. There should be at least one sample point per 1 000 square kilometers.

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